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Large-tow carbon fiber-reinforced polymer composites (CFRP) have great application potential in civil engineering due to their low price, but their basic mechanical properties are still unclear. The tensile properties of large-tow CFRP rods and plates were investigated in this study. First, the tensile properties of unidirectional CFRP rods and plates were studied, and the test results of the relevant mechanical properties were statistically analyzed. The tensile strength of the CFRP rod and plate are 2005.97 MPa and 2069.48 MPa. Second, the surface of the test specimens after failure was observed using a scanning electron microscope to analyze the type of failure and damage evolution process. Finally, the probabilistic characteristics of the mechanical properties were analyzed using normal, lognormal, and Weibull distributions for parameter fitting. Quasi-optimality tests were performed, and a probability distribution model was proposed for the mechanical properties of large-tow CFRP rods and plates. [ABSTRACT FROM AUTHOR]

While the high-voltage direct current (HVDC) transmission system is in monopolar operation, it produces thousands of amperes of ground-return currents (GRCs). Accurate computation of the GRCs is essential for assessing safety implications for nearby industrial infrastructure. Current three-dimensional forward models of GRCs are typically constructed based on discrete differential equations, and their solving efficiency is constrained by the increased degrees of freedom resulting from the fine discretization grids in high-conductivity conductors and ground points. To address this issue, we present a new resistor network (RN) forward solver based on a multi-resolution grid approach. This solver utilizes an RN to avoid the massive degrees of freedom resulting from fine discretization of high-voltage conductors and enhances grid discretization efficiency near the surface grounding system through multi-resolution grids. We demonstrate, through multiple three-dimensional geoelectrical model cases, that the proposed method reduces the forward modeling misfit to 1% and possesses only 3‰ of the required discrete elements compared to traditional approaches. Furthermore, practical HVDC grid model analyses indicate the successful application of the proposed method for GRC analysis in complex geoelectric conditions. [ABSTRACT FROM AUTHOR]

Complex optimization problems hold broad significance across numerous fields and applications. However, as the dimensionality of such problems increases, issues like the curse of dimensionality and local optima trapping also arise. To address these challenges, this paper proposes a novel Wild Gibbon Optimization Algorithm (WGOA) based on an analysis of wild gibbon population behavior. WGOA comprises two strategies: community search and community competition. The community search strategy facilitates information exchange between two gibbon families, generating multiple candidate solutions to enhance algorithm diversity. Meanwhile, the community competition strategy reselects leaders for the population after each iteration, thus enhancing algorithm precision. To assess the algorithm's performance, CEC2017 and CEC2022 are chosen as test functions. In the CEC2017 test suite, WGOA secures first place in 10 functions. In the CEC2022 benchmark functions, WGOA obtained the first rank in 5 functions. The ultimate experimental findings demonstrate that the Wild Gibbon Optimization Algorithm outperforms others in tested functions. This underscores the strong robustness and stability of the gibbon algorithm in tackling complex single-objective optimization problems. [ABSTRACT FROM AUTHOR]